Objectives: To analyze the allometric scalling for BM and the height under 20 years old. Methods: Individuals 0-20 years of the National Health and Nutrition Examination Survey (NHANES-1999-2013); Pesquisa Nacional de Saúde e Nutrição (PNSN-1989); Encuesta de Salud y Nutrición (2012); England Health Survei (2005-2014) and; Korean National Health and Nutrition Examination Survey (KNHANES-1998-2014). BM and height were converted to logarithmic scale and modeled by linear regression, in 24 age groups, 2 sexes and 5 countries. The β of this regression gave the estimated p value in 2 steps. 1) All data available in the surveys, excluding only those biologically implausible values; and 2) The value was obtained after the exclusion of values not expected for age (VNEA) of MC and height. VNEA was defined as ± 2.0 SD (z) cases of regression of BM by age, height by age and MC by height. Then, the values were modeled by spline in 5 knots, to define an international (ip). After were calculated the AI - Allometric Index for all individuals. The Pearson correlation (r) between the indices and the fat mass was calculated used data dorm densitometry (DXA), Bioelectrical Impedance (BIA), Waist Circumference (WC) and Skin Folds (SF). In an analysis of mixed effects, was estimated the intraclass correlation coefficient (ICC), between countries and ethnicities for different dimensions for BM, BMI and AI. Results: Exclusion of VNEA (8.5% of the sample) decreased the difference between countries. The p and ip presented values close to 2 at birth, increased to 3 to 3.5 (7 and 11 years in girls and 8 to 12 in boys) and recorded 2 at the end of growth. AI was close to zero in correlation with height and for BMI was r= 0.4 during puberty. The correlation of the adipose mass for the two indices was similar, always presenting r above 0.85 for all forms of analysis via DC, BIA, CC and DXA. AI presented a lower correlation with muscle mass and bone density. ICC is larger among countries and is practically zero among ethnicities. The greatest difference between the groups was the height, the BM and the BMI. AI showed the smallest difference between the countries (3.6%) and between the ethnic groups (1.7%). Conclusions: A VNEA exclusion contributed to decrease the effect of nutritional status on allometry to estimate the p value. The value ip has proved to be a promising value for international use. The IA in the body of evidence has an advantage over BMI, since it has correlation 0 with height, and a correlation equivalent to the BMI with the adipose mass besides presenting the lowest CCI between ethnicities and nationalities. The greatest variation of ICC was borne by the country in relation to height, justified by the different epidemiological contexts.

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